Presenter:

Minsu Kim(Emory University)

Authors:

Jessica Coates(Emory University)

Bo Ryoung Park(Emory University)

Dai Le(Emory University)

Emrah Simsek(Emory University)

Minsu Kim(Emory University)

Frequent antibiotic failure is a serious threat to public health. To cope with this threat, it is critical that we better understand the population dynamics of bacteria exposed to antibiotics. Previous studies have extensively characterized the homogenous dynamics of large bacterial populations exposed to antibiotics, establishing the deterministic framework of pharmacodynamics. However, the outcome of antibiotic treatment is typically far from being deterministic. Here, characterizing small bacterial populations, we demonstrate the stochastic nature of bacterial clearance using antibiotics. We found that bactericidal drugs induce population fluctuations, leading to stochastic population dynamics. Consequently, bacterial clearance does not follow a deterministic course but is highly probabilistic. The probability of the clearance was well captured by the birth-death Markov model. The model also predicted an increase in the probability of clearance with a decrease in growth rate. We experimentally tested this prediction. Our study reveals the stochastic population dynamics induced by antibiotics and how this stochasticity may be manipulated to facilitate bacterial clearance.

*We acknowledge support from Research Corporation for Science Advancement.

To cite this abstract, use the following reference: http://meetings.aps.org/link/BAPS.2018.MAR.H49.1